Tatsuya Koyakumaru

A Graph Learning Algorithm Based On Gaussian Markov Random Fields And Minimax Concave Penalty

This paper presents a graph learning framework to produce sparse and accurate graphs from network data. While our formulation is inspired by the graphical lasso, a key difference is the use of a nonconvex alternative of the ℓ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://ww…